Absolute penalty and shrinkage estimation in partially linear models

DOI10.1016/j.csda.2011.09.021zbMath1243.62058OpenAlexW1972278166MaRDI QIDQ433248

Kjell A. Doksum, S. Ejaz Ahmed, S. M. Enayetur Raheem

Publication date: 13 July 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.09.021

zbMATH Keywords

James-Stein estimatorsemiparametric modelMonte Carlo simulationlassoB-spline approximationabsolute penalty estimationadaptive lasso

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Monte Carlo methods (65C05)

Related Items (13)

Penalty, post pretest and shrinkage strategies in a partially linear model ⋮ The risk of tensor Stein-rules in elliptically contoured distributions ⋮ Inconsistency transmission and variance reduction in two-stage quantile regression ⋮ Counterfactual distributions of wages via quantile regression with endogeneity ⋮ Pretest and shrinkage estimators in generalized partially linear models with application to real data ⋮ Asymptotic properties of wavelet estimators in partially linear errors-in-variables models with long-memory errors ⋮ Shrinkage estimation for the mean of the inverse Gaussian population ⋮ Shrinkage ridge estimators in semiparametric regression models ⋮ Nonparametric Shrinkage Estimation for Aalen's Additive Hazards Model ⋮ Shrinkage and LASSO strategies in high-dimensional heteroscedastic models ⋮ Shrinkage and penalized estimation in semi-parametric models with multicollinear data ⋮ Ridge-type pretest and shrinkage estimations in partially linear models ⋮ Shrinkage and pretest estimators for longitudinal data analysis under partially linear models

Uses Software

• R
• car
• glmnet
• ElemStatLearn

Cites Work

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• The Adaptive Lasso and Its Oracle Properties
• Estimation in partially linear models and numerical comparisons
• Robust inference strategy in the presence of measurement error
• Least angle and \(\ell _{1}\) penalized regression: a review
• Polynomial spline estimation of partially linear single-index proportional hazards regression models
• Bivariate tensor-product \(B\)-splines in a partly linear model
• Consistent covariate selection and post model selection inference in semiparametric regression.
• Regression function estimation from dependent observations
• SHRINKAGE, PRETEST AND ABSOLUTE PENALTY ESTIMATORS IN PARTIALLY LINEAR MODELS
• Asymptotic theory for partly linear models
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Stability Selection
• Asymptotic Expansion of the Coverage Probability of James–Stein Estimators
• A Semiparametric Basis for Combining Estimation Problems Under Quadratic Loss
• A practical guide to splines.

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